DeepSDFStruct.torch_spline#
Functions
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Takes bounding box and generates a spline box. |
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Evaluate a 3D B-spline volume at query points. |
Classes
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V2: uses custom torch spline as spline backend |
- class DeepSDFStruct.torch_spline.TorchSpline(spline, device='cpu', dtype=torch.float32)#
Bases:
torch.nn.modules.module.Module
V2: uses custom torch spline as spline backend
- Parameters:
spline (splinepy.bspline.BSpline)
- forward(queries)#
Define the computation performed at every call.
Should be overridden by all subclasses.
Note
Although the recipe for forward pass needs to be defined within this function, one should call the
Module
instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.- Parameters:
queries (torch.Tensor)
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spline:
BSpline
#
- DeepSDFStruct.torch_spline.bspline_basis(t, p, queries)#
- Parameters:
queries (torch._VariableFunctionsClass.tensor)
- DeepSDFStruct.torch_spline.generate_bbox_spline(bounds)#
Takes bounding box and generates a spline box.
- Parameters:
bounds ((2, 3) array-like) –
- [[xmin, ymin, zmin],
[xmax, ymax, zmax]]
- Returns:
spline – BSpline representing the bounding box.
- Return type:
splinepy.BSpline
- DeepSDFStruct.torch_spline.torch_spline_1D(knot_vectors, control_points, degrees, queries)#
- Parameters:
queries (torch._VariableFunctionsClass.tensor)
- DeepSDFStruct.torch_spline.torch_spline_3D(knot_vectors, control_points, degrees, queries)#
Evaluate a 3D B-spline volume at query points.
- Parameters:
tx – knot vectors for x, y, z
ty – knot vectors for x, y, z
tz – knot vectors for x, y, z
px – degrees
py – degrees
pz – degrees
cp – control points, shape (nx, ny, nz, d)
qx – query coordinates, shape (N,)
qy – query coordinates, shape (N,)
qz – query coordinates, shape (N,)
- Returns:
evaluated spline, shape (N, d)
- Return type:
y